Polyhydroxyalkanoates production from short and medium chain carboxylic acids by Paracoccus homiensis

The aim of this study was to evaluate an effect of short and medium chain carboxylic acids (CAs) rich stream derived from acidogenic mixed culture fermentation of acid whey on polyhydroxyalkanoates (PHAs) synthesis by Paracoccus homiensis and compare it with the impact of individual synthetic CAs. The obtained results confirmed that the analyzed bacterium is able to metabolize synthetic CAs as the only carbon sources in the growth medium with maximum PHAs production yields of 26% of cell dry mass (CDM). The replacement of the individual CAs by a CAs-rich residual stream was found to be beneficial for the Paracoccus homiensis growth. The highest biomass concentration reached about 2.5 g/L with PHAs content of 17% of CDM. The purified PHAs were identified as poly(3-hydroxybutyrate-co-3-hydroxyvalerate) by applying gas chromatography coupled with mass spectrometry, Fourier transform infrared spectroscopic spectra and UV–Vis spectra. Furthermore, a differential scanning calorimetric, thermogravimetric and water contact angle analysis proved that the extracted copolymers have useful properties. The obtained data are promising in the perspective of developing a microbial PHAs production as a part of an integrated valorization process of high CAs content waste-derived streams.

concentration of individual CAs that guarantee the effective growth of the Paracoccus homiensis and efficient PHAs production, the culture medium was supplemented with the different concentrations of acetic acid, propionic acid, butyric acid, valeric acid and caproic acid. The same growth medium conditions and the amount of inoculum were maintained in all cultivations.
As shown in Fig. 1A,B all tested CAs were utilized to support cell growth and PHAs synthesis and accumulation. During all cultivations, the growth rate depended on the individual CAs concentration. In all experiments, the maximum specific growth rate (μ max ) reached a higher value than 0.1/h (Fig. 1B). Using 2 g/L of acetic acid, both maximum μ max (0.87/h) and biomass concentration (1.6 g/L) were obtained. It was previously suggested that acetic acid is less toxic and could be easier metabolized by bacteria than other tested CAs 18 . Saraphirom et al. 19 revealed that when acetic acid is present in the medium microorganisms prefer to utilize acetic acid than butyric acid. Our study showed that the addition of 2 g/L of propionic acid or valeric acid also resulted in higher biomass concentration compared to other analyzed concentrations of these CAs. For butyric and caproic acids the most preferable concentration to support the bacterial growth was 1 g/L, at this level the CDM values reached 1.4 and 1.3 g/L, respectively. Moreover, the results confirmed that with an increase of all CAs concentration to 4 g/L, μ max and CDM value decreased. However, the CDM concentration was higher at 48 h of all treatments www.nature.com/scientificreports/ compared with 24 h. The reported differences in the μ max values were related to different metabolic pathways that were involved in the utilization of CAs. Acetic acid, present in the culture medium can be initially converted to acetyl-CoA which is one of an intermediate in PHA synthesis. Then, two acetyl-CoA moieties are transformed to acetoacetyl-CoA which is needed for the synthesis of 3HB monomer. This monomer could be directly synthesized via acetoacetyl-CoA when butyric acid is present in the growth medium. For propionic acid the carbonyl carbon of propionyl-CoA is eliminated that enable to synthesize both 3HB and 3HV units 20 .
Our results indicated that the PHAs content in P. homiensis cells was dependent on the type and concentration of individual CAs. The analyzed bacteria were able to produce PHAs in all conducted cultivations with CAs. As expected, no PHAs were synthesized in bacterial cells grown on Bacto Marine Broth (treated as a control). As may be observed from data reported in Fig. 2 the highest PHAs production was obtained when acetic acid was added as a single carbon source. However, the statistically significant difference (P = 0.014) was found only between cultivations supplemented with acetic and butyric acid. The best accumulation of the PHAs from this CA was achieved at 3 g/L (26.1% of CDM). Also, this concentration was ideal for PHA production by P. homiensis grown on propionic acid, however, about 1.6 fold lower PHA accumulation value was observed compared with acetic acid. The bacteria could efficiently metabolized valeric acid at 4 g/L to produce higher content of the biopolymer (18.9% of CDM) compared to other concentrations of this substrate. PHA synthesis and accumulation by P. homiensis was inhibited as the caproic acid concentration increased reaching 20.3% and 13.7% of CDM at 1 g/L and 4 g/L, respectively. This could be due to inhibitory effect of the substrate for the accumulation mechanisms of the analyzed bacterial cells. Too high CAs level could have reduced the proton gradient across the cell membrane and increased osmotic pressure of the cells due to their need to pump out anions to survive under acidic pH conditions in the growth medium. Moreover, the presence of organic acids in cytoplasm results in releasing protons that caused its acidification and more energy is used to maintain the gradient inside the cell 14 . Thus, higher CAs concentration used in our study may have resulted in low acid utilization and PHA concentration. Therefore, the optimization conducted within our studies seems to be essential as the undissociated CAs molecules could enter the cytoplasm and in a consequence could be activated and utilized into CO 2 , bacterial cell growth or PHA synthesis only when CAs are present at appropriate levels 21,22 . Thus, CAs concentration should be carefully regulated during bacterial cultivations. In general, the lowest biopolymer content in all treatments was observed when the bacteria were cultured on butyric acid at all analyzed concentrations (from 9.7 to 10.1% PHAs of CDM). Kedia et al. 23 have also revealed the inhibitory effect of butyric acid for PHAs storage ability by Cupriavidus necator, a lower PHA concentration was observed when this acid was used as the only substrate compared to acetic acid. Nevertheless, these results are not in accordance with the data reported by Chakraborty et al. 24 for Ralstonia eutropha which grown on butyric acid and yielded the best results of PHA concentration compared to acetic acid. It could be suggested that for P. homiensis butyric acid is not energetically efficient as other CAs for biopolyesters synthesis and accumulation. Furthermore, the cell mass concentration could be the primary factor that affect this acid tolerance of the analyzed bacteria 25 . During the P. homiensis growth in the medium supplemented with butyric acid, the lowest CDM level was achieved.
Growth and PHAs using CAs-rich stream. Studies on CAs utilization for the PHA biosynthesis by P. homiensis have not been described in literature so far. The production of these biopolyesters by other wellknown microorganisms are limited to the use of individual synthetic CAs. Therefore, to determine the effect of CAs derived from acid whey in more detail, CAs-rich stream was added to the Bacto Marine Broth at varying concentrations (from 5 to 30% v/v). During all cultivations, an increase in the absorbance of the cultures was observed. The highest μ max (0.16/h) and CDM (2.5 g/L) value was determined when 30% of CAs-rich stream was added to the culture broth (Fig. 3A,B). PHA production was observed under all CAs-rich stream concentrations. At 24 h, the PHAs content decreased when the carbon source concentration increased (from 7.7 to 2.7% of CDM). However, at the end of the experiments, the PHAs content was the highest in P. homiensis cells cultivated in culture medium containing 25% CAs-rich stream, about 16.7% of CDM. As may be observed in Fig. 3C, the further increase of the concentration of this waste carbon source resulted in a decrease of PHAs www.nature.com/scientificreports/ content. PHAs were detected in a trace amount in the bacterial cells cultured in the medium supplemented with 30% CAs-rich stream (5.3% of CDM). Relatively lower PHA content from CAs-rich stream compared to the individual CAs proved that CAs-rich stream had more inhibitory effect due to its complexity. The inhibition of PHA biosynthesis could have been caused by the CAs-rich stream which may interfered with the proton gradient mechanism 15 . Furthermore, quite low PHA productivity could be explained by the presence of butyric acid as the dominant component in the CAs-rich stream which as a single carboxylic acid in the medium resulted in the lowest PHAs production efficiency compared with others. It should be also noted that the presence of high CAs concentration can reduce growth rate, therefore most researchers add such carbon sources after reaching by bacteria its maximum growth, whereas in our study CAs-rich stream was added at the beginning of the cultivations. Furthermore, the experiments were conducted in 250-mL shake flasks in which a control of the parameters like aeration rate, pH value is not possible. It could be presumed that the above mentioned factors might have affected achievement of higher PHA concentration. However, the obtained PHA content was about twofold higher than that reported by Vu et al. 16 who cultivated Bacillus megaterium also on the CAs-rich stream from the acidogenic fermentation of food waste. To improve the PHA yields, CAs feeding adjustment, optimization of oxygen, pH control is needed.
Characterization of extracted PHA copolymers. PHA biopolymer repeat-units composition. The extracted PHAs from all performed cultivations fed with individual CAs and CAs-rich stream were subjected to gas chromatography analysis to provide information about their repeat-units composition (Table 1). Our data indicate that the monomeric composition varied with the carbon sources concentration and the monomers content was changeable at different process time.
The obtained results proved that P. homiensis cultured on acetic acid and caproic acid showed a tendency to synthesize the biopolymer consisted of high 3HB monomer and lower 3HV monomer for all concentrations and both time intervals. The 3HV content increased with prolonging the process time. The data revealed that the P. homiensis fed at 2 g/L of propionic acid and 4 g/L of butyric acid produced P(3HB) homopolymer. At other concentrations of those carboxylates the 3HB and 3HV monomers were detected. However, higher 3HV content was observed in the cultivations with propionic acid at both 24 h and 48 h of the processes. The highest 3HV content was confirmed in the P(3HB-co-3HV) copolymer extracted from the cells grown on valeric www.nature.com/scientificreports/ acid. The 3HV content was higher than 3HB content at both 24 and 48 h and this fraction showed higher share with increase in valeric acid concentration, from 59.9 to 85.3 mol% at 24 h and from 62.4 to 87.0 mol% at 48 h. Our data showed that the utilization of CAs-rich stream led to the synthesis and accumulation of the P(3HBco-3HV) copolymer. Due to the presence in the CAs-rich stream high amounts of acetic acid and butyric acid, low concentration of valeric acid, and the absence of propionic acid the extracted copolymer consisted of the lower 3HV content than 3HB. Furthermore, the GC results proved that the 3HV content was higher at 24 h compared to 48 h (P = 0.045). At 24 h of cultivation, the 3HV content was positively correlated with the CAsrich stream concentrations (Spearman's correlation coefficient = 0.83). Surprisingly, the highest 3HV content (7.5 mol%) was observed when 20% of CAs-rich stream was added. At 48 h correlation between the 3HV content and the CAs-stream concentrations was not observed. Generally, higher 3HV content was observed when higher CAs-stream concentrations were applied. The possibility of the copolymer production using CAs-rich stream is very attractive since pure P(3HB) has limited applicability due to similar melting and degradation temperatures 26 . However, the 3HV content in the extracted polymers was not sufficiently high, therefore to increase the level of this monomer the induction of the acidogenic fermentation to produce more CAs with an odd carbon number would be beneficial 15 .
FTIR spectra. In the FTIR spectra, several bands have been observed that can be assigned to functional groups characteristic for P(3HB-co-3HV) copolymer 27 . The spectra of PHAs samples extracted from the cultivations with acetic, propionic, butyric, caproic acid and CAs-rich streams were similar and only in the case of P(3HB-co-3HV) sample from valeric acid some differences were observed. FTIR spectra of the analyzed samples were recorded in the range from 4000 to 700 cm −1 (Supplementary materials 1). A band with a maximum of ~ 3333 cm −1 was observed only for the PHA sample produced by P. homiensis grown on valeric acid. It probably originates from terminal -OH groups present at the ends of the polymer chains. The presence of this band confirms earlier assumptions about the large number of shorter macromolecules (oligomers). The band in the range 3100-2700 cm −1 is associated with the presence of the -CH 3 and -CH 2 groups. Clearly larger peaks with a maximum of ~ 2925 and ~ 2852 cm −1 in this material are due to the higher content of 3HV units, which con- Table 1. Monomeric composition of PHAs produced by P. homiensis grown on synthetic and waste derived short and medium chain carboxylic acids. 3HB, 3-hydroxybutyrate; 3HV, 3-hydroxyvalerate; CAs, carboxylic acids. %* -an unit of the concentration of CAs-rich stream Unlike the other extracted biopolyesters in the produced copolymer using valeric acid, instead of the ~ 1278 and ~ 1228 cm −1 peaks, one high intensity peak derived from C-O-C bonds was recorded with a maximum at 1263 cm −1 . The observed changes are related to the high crystallinity degree of this biopolymer. Peaks ~ 1278 and ~ 1228 cm −1 are very sensitive to the content of the crystalline phase 28 . In the amorphous materials in the 1330-1230 cm −1 range two peaks are observed, while for semi-crystalline materials only one 29 .
UV-VIs absorbance spectra. The spectra of the UV-VIs absorbance revealed three absorbance peaks attributed to the wavelength range from about 200 to about 400 nm (Supplementary Materials 1). The absorption bands structure is similar to the samples representing typical absorption bands for 3HB. The polymers, extracted from the bacterial cells cultured on acetic, propionic, butyric and caproic acid, showed high 3HB content (above 93%) and low 3HV content. Except for the P(3HB-co-3HV) sample from valeric acid, for which only very insignificant absorption bands were identified in that spectra region. This resulted most likely from the different chemical structure of this biopolymer for which the 3HB content is significantly reduced (only about 17 mol%).
Physico-thermal properties of extracted PHAs. The extracted PHAs properties determine which applications these materials are best suited for and how they can be processed. Therefore, in this work, the influence of the CAs on the thermal properties of the accumulated PHAs was also analyzed ( Fig. 4; Table 2; Supplementary materials 1). Cooling curves, and therefore the nature of changes in the material as a result of cooling, of individual materials followed one of four types. In the first type, only the inflection related to the glass transition of the tested biomaterial was observed on the cooling curve. This type was determined for PHAs extracted from the bacteria cells grown on propionic and caproic acid. The T g values determined from the cooling curves of these materials were − 3.9 and − 6.3 °C, respectively.
In the second type of cooling curve, in addition to a clear glass transition inflection, an exothermic peak associated with the crystallization of the biomaterial was also observed. This type occurred in PHAs from the cultivation supplemented with acetic and butyric acid, with the crystallization peak being much larger for the PHAs produced using acetic acid, which indicates a more intense crystallization process and more crystalline phase formation. The determined T g and T c values were − 6.6 and 52.9 °C for the biopolymer synthesized using acetic acid and − 5.6 and 46.6 °C using butyric acid.
A third type of cooling curve pattern was observed for the PHAs extracted from the bacterial cells grown on valeric acid. The T g of this biopolymer was − 3.1 °C. Also, for this biomaterial an exothermic crystallization peak was revealed on the cooling curve. However, the crystallization peak was bimodal with clearly visible two arms of similar intensity with a maximum at 32.3 and 48.9 °C. The reason for the bimodal peak of crystallization may be the high content of 3HV mers, which significantly affected the nature of this process or the presence of a large number of macromolecules with a much lower molecular weight (oligomers). As a result, two crystalline phases with different structure and/or composition of crystallites having different crystallization temperatures may be formed during cooling.
The fourth type of cooling curves was observed for polymers obtained from CAs-rich stream. The course of the cooling process was very similar to the course of polymers obtained from acetic and butyric acid. However, the temperatures of the crystallization process and the intensity of the process were much higher. The highest crystallization temperature for this group of polymers was 65.4 °C and the enthalpy value of the crystallization www.nature.com/scientificreports/ process was 54.1 J/g. However, it was not possible to determine the glass transition for these samples due to the low intensity of this process. The heating curves of the analyzed biopolymers were similar. The inflections and exothermic or endothermic peaks typical for the occurrence of glass transition, cold crystallization and melting of the crystalline phase processes were observed on all curves. T g values determined from the second heating curves of individual biomaterials ranged from − 1.4 (PHAs from caproic acid) to 2.5 °C (PHAs from 15% CAs-rich stream), which agrees with the literature values that have been shown for a P(3HB-co-3HV) copolymer 30,31 .
Regardless of the nature of the crystallization during cooling, all biopolyesters showed a tendency to cold crystallization, which was the cause of the exothermic peak observed on the curves. T cc values were ranged from 33.4 (PHAs from valeric acid) to 45.0 °C (PHAs from 30% CAs-rich stream). An interesting two-stage course of the cold crystallization process was observed for polymers obtained from CAs-rich stream. In the initial phase of cold crystallization there was a slight peak at about 40 °C, then the process was less intensive in a wide temperature range, which was reflected in an exothermic peak of low intensity ranging from 50 to 120 °C with a maximum around 90 °C. More significant changes were observed in the intensity of the cold crystallization process, which resulted from the course of the crystallization during cooling.
The lowest ΔH cc value of 17.0 J/g was obtained for PHAs extracted from the analyzed strain grown on valeric acid, which is probably due to the different composition of this sample (high content of 3HV units) and its negative impact on susceptibility to cold crystallization. The remaining samples had significantly higher ΔH cc values ranging from 47.2 (PHAs from acetic acid) to 68.9 J/g (PHAs from butyric acid). The course of the cold crystallization process depended on the course of the crystallization during cooling. The lower the intensity of the crystallization process during cooling, the greater the peak of cold crystallization, and therefore the intensity of this process.
The last phase change observed in the studied temperature range was the melting of the crystalline phase seen as an endothermic peak. The highest T m value of 168.1 °C was obtained for PHAs from valeric acid, which were also characterized by a high value of ΔH m . This data proved the high intensity of this process and the high content of the crystalline phase. The degree of crystallinity of this sample was 51.2% and was the highest among all tested biomaterials. In addition, a second endothermic melting peak, not found in other samples, with a maximum at 53.6 °C and ΔH m of 6.3 J/g was observed on the heating curve of this biopolymer. The low melting point of this peak suggests that the most likely reason for its occurrence is the melting of lower molecular weight macromolecules (oligomers), which at the same time suggests that they are the cause of the bimodal crystallization peak during cooling.
Similar melting temperatures were obtained for PHAs extracted from the cultivations supplemented with acetic acid and butyric acid. The T m values of these biopolymers were 165.0 and 165.8 °C, respectively. Although the difference in ΔH m was only about 7 J/g, they differed significantly in the degree of crystallinity. The calculated X c values were 29.0 and 2.9%, for PHAs from acetic acid and butyric acid, respectively. These differences resulted from the crystalline phase formation stage. In the case of PHAs from butyric acid, most of the crystalline phase is formed during the cold crystallization process, so it is practically non-existent in the starting material suggesting it is amorphous. Whereas, in PHAs from acetic acid, most of the crystalline phase is formed during the cooling of this material, so the crystalline phase already occurs before it is heated, indicating that it is semi-crystalline.
The melting temperatures of the polymers obtained from CAs-rich stream ranged from 161.4 to 166 °C. However, the biggest difference compared to other polymers was the presence of a distinct second melting peak Table 2. Thermal properties of PHAs using short and medium chain carboxylic acids as the only carbon sources. nd, not detected. a A distinct and separate, second crystallization and melting peak. b A second cold crystallization peak. www.nature.com/scientificreports/ around 150 °C. The appearance of the second melting peak resulted from the two-stage process of cold crystallization, in which two crystalline phases with distinctly different melting points were formed. The degree of crystallinity of the polymers obtained from the cultivations with waste derived CAs ranged from 25.0 to 52.7%. Lower melting temperatures and melting enthalpy changes were obtained for PHAs extracted from the cultivations with propionic and caproic acid. The T m and ΔH m values were 158.9 °C and 62.5 J/g, and 155.4 °C and 60.4 J/g, respectively. The intensity of the melting process of these samples was therefore similar, which with a similar course of the crystallization and the cold crystallization processes resulted in a similar degree of their crystallinity. The X c values of these biopolymers were less than 3%, indicating that the starting materials had an amorphous structure. Figure 5 shows the TG and DTG curves of selected samples (PHAs from acetic acid, valeric acid, caproic acid and 5% of CAs-rich stream, the remaining ones are shown in Supplementary materials 1). The curves of the remaining samples are similar and correspond to one of the presented, so they were not added. The numerical results of TG measurements of all samples are shown in Table 2. In the analysis of test results, as the temperature of material degradation enabling determination of its thermal resistance, a temperature of 5% loss of the mass of the tested sample was assumed (T 5% ). The T 5% depended on the characteristic of the weight loss process and ranged from 238.0 (PHAs from 5% CAs-rich stream) to 184.0 °C (PHAs from valeric acid).
The biopolymer extracted from the cultivation supplemented with CAs-rich stream had the highest thermal resistance among all tested biomaterials. The T 5% of those polymers ranged from 221.9 to 238.0 °C. The highest crystalline phase content among these tested biopolyesters, characterized by greater thermal resistance than the amorphous phase, was probably the reason for the highest thermal resistance of this materials. However, as the concentration of CAs-rich stream increased, the thermal resistance of the extracted biopolymers decreased, www.nature.com/scientificreports/ despite even higher degree of crystallization. T 5% dropped to 221.9 for PHAs obtained from 30% of CAs-rich stream. Similar high thermal resistance was observed for the biopolymer extracted from the cultivation supplemented with acetic acid. The T 5% was 232.4 °C, and the highest rate of weight loss occurred at T max 262.0 °C. High thermal resistance, as in the case of PHAs obtained from CAs-rich stream, resulted from the high degree of crystallinity of this material. Noteworthy is the high thermal resistance of PHAs obtained from the cultivations using propionic acid. It is similar to the resistance of PHAs extracted from the cultures with acetic acid and CAs-rich stream, despite a much lower degree of crystallinity. These polymers are characterized by a higher content of 3HV units and this may be the reason for the observed increase in thermal resistance.
The P(3HB-co-3HV) produced in the bacterial cultivations with butyric acid and caproic acid had lower thermal resistance (T 5% values were 215.9 and 218.9 °C, respectively) suggesting that the onset of thermal degradation of these materials was similar. However, these biopolymers differed significantly in the rate of degradation process. The T max value of PHAs from caproic acid was 253.9 °C, while the value of PHAs from butyric acid was lower by more than 20 °C and was the smallest among all tested biomaterials indicating that it has the lowest thermal stability. Low T 5% of the above mentioned copolymers were due to the characteristic of the weight loss process. Based on the TG curves, it can be seen that the degradation is a two-step process. In the first step, a slight decrease of about 5% of the sample mass were observed, followed by a second step with rapid mass loss. The cause of the initial slight weight loss may be small-molecule compounds characterized by lower degradation temperatures contained in the biomaterial, which are residues after the synthesis process or macromolecules with shorter polymer chains. For the PHAs from valeric acid a loss of 5% of sample weight occurred already at 184.0 °C because of a high content of smaller macromolecules (oligomers). It was also confirmed by DSC analysis as well as observed evident two-step characteristic of weight loss, which in the first stage was as much as 8%. However, further rate of the mass change was similar to the other samples, which is proved by the T m value of 253.9 °C.
Water related properties of extracted PHAs. The obtained water contact angles and calculated value of surface energy (SE) of the extracted biopolymers were summarized in Table 3. For the PHA-copolymer from propionic acid water droplet was rapidly dispersed on the surface, thus the results were not presented. As shown in Table 3 the smallest water contact angles was detected for the PHAs extracted from the P. homiensis cells cultured on acetic acid. The average contact angle of 29.5° suggested that this sample had strong hydrophilic properties and a high surface energy value. Whereas, the highest average water contact angle was observed for the PHAs from butyric acid indicating their high hydrophobic properties.

Conclusion
Inexpensive carbon sources are essential to make the PHA production process economically feasible. Our results indicated that P. homiensis has the potential to convert CAs into PHAs which have not been reported before. As the use of pure CAs would be costly, we propose the novel idea of utilizing CAs-rich stream derived from acidogenic mixed culture fermentation of agro-industrial waste without necessity for substrate pretreatment for production of P(3HB-co-3HV) copolymer. The structure of the copolymer was analytically verified and we found that the extracted biopolymers have properties that are beneficial for industrial applications. The obtained results proved that all copolymers produced by P. homiensis possessed good thermal stability. However, the P(3HBco-3HV) extracted from the cultivations supplemented with CAs-rich stream had the highest thermal resistance. These polymers show a relatively wide processing thermal window, since the difference between melting temperature and degradation temperature is higher compared to the polymers extracted from the cultivations with synthetic CAs. However, to maximize PHA production, it would be essential to extend the knowledge on metabolic pathways in P. homiensis that are engaged in the biopolymers synthesis. Carbon sources and culture conditions for PHA production. The carbon source in the culture medium were individual CAs (acetic acid, propionic acid, butyric acid, valeric acid and caproic acid) and CAsrich stream from MCF of acid whey. Acid whey was collected from a crude cheese production line, upon usage, feedstock was stored at 4 °C. The CAs production was carried out in a 1 L working volume UASB bioreactor constructed from cylindrical plexiglass with recirculation ensuring biomass suspension as described before in Duber et al. 32 . The process was carried out at constant temperature of 30 °C and constant pH of 5.5 with automatic control using 2 M NaOH. The effluent for PHAs production was taken from a steady-state phase with high butyrate production and its characteristics were as follows: acetic acid (2.85 g/L), butyric acid (9.86 g/L), valeric acid (0.16 g/L), caproic acid (3.05 g/L), lactic acid (9.31 g/L), and ethanol (1.64 g/L).
The flask experiments were conducted in triplicate in 250 mL Erlenmeyer flasks containing 100 mL of Bacto Marine Broth (the composition described above) supplemented with varying concentration of individual CAs from 1 to 4 g/L and CAs-rich stream from 5 to 30% v/v. The CAs were added at the beginning of the cultivations. Fermentation shake flasks were inoculated with 5% v/v of the seed and were subsampled for PHA production. The cultivation with Bacto Marine Broth was treated as a control. All experiments were conducted in a rotary shaker at 110 rpm and the bacteria were incubated at 28 °C for 48 h. The cells were harvested to determine the optical density value, cell concentration, PHAs content and physico-chemical analysis of the purified biopolymers.
Analytical procedures. Cell growth was monitored by measuring absorbance at 600 nm (OD 600 ) using a spectrophotometer (Eppendorf, Germany). To obtain more accurate information on the growth of the test strain, the maximum specific growth rate (μ max ) was determined as an equation for the linear trend line for the exponential phase. Linearization was made in which the slope of the linear regression gives μ max in 1/h. To estimate cell dry mass (CDM), culture samples were harvested at 24 and 48 h and centrifuged at 9000 × g for 10 min. Next, the supernatant was removed and the biomass pellet was lyophilized for 24 h using Lyovac GT2 System (SRK Systemtechnik GmbH, Riedstadt, Germany). PHAs were extracted from lyophilized cells by shaking in hot chloroform at 50 °C for 3 h. Then, the mixture was filtered through No. 1 Whatman filter paper to remove cellular debris. Biopolymers dissolved in chloroform were purified by precipitation with 70% cold methanol and then allowed to evaporate at room temperature. The biopolymer content (% of CDM) was defined as the percentage of the ratio of PHAs concentration to total cell concentration.
PHAs analysis. The monomeric composition of produced PHAs was determined by gas chromatography coupled with mass spectrometry (GC-MS QP2010 PLUS, Shimadzu, Japan) according to the method described by Możejko-Ciesielska and Pokój 33 . Firstly, the analyzed samples were suspended in mixture: chloroform-methanol-sulfuric acid (100/97/3, v/v/v) and methylation was done by heating the vials at 100 °C for 20 h. Then, sulfuric acid neutralize with Na 2 CO 3 addition and obtained mixture was dried with anhydrous Na 2 SO 4 . After filtration methyl esters were analyzed with the use of a BPX70 (25 m × 0.22 mm × 0.25 mm) capillary column (SGE Analytical Science, Victoria, Australia) with helium as a carrier gas at a flow rate of 1.38 mL/min. The column was uniformly heated from 80 to 240 °C at the rate of 10 °C/min. The interface and ion source temperatures of GC-MS was set at 240 °C, and the electron energy was set at 70 eV. The total ion current (TIC) mode was used in 45-500 m/z range. Known quantities of pure 3-hydroxyacids standards (Larodan, Sweden) were used in quantitative analysis.
Infrared spectroscopy studies were performed using a FTIR Nicolet iS10 spectrophotometer (Thermo Scientific, USA). Fourier transform infrared spectroscopic spectra (FTIR) were obtained by attenuated total reflection (ATR-FTIR). Each analyzed spectrum was the average of 16 measurements recorded in the wave number range from 4000 to 650 cm −1 . UV-Vis spectra were recorded on a spectrometer Evolution 220 (Thermo Scientific, USA) equipped with an integrating sphere. Each analyzed spectrum was the average of 16 measurements recorded in the wavelength from 200 to 1100 nm.
Differential scanning calorimetry (DSC) tests were carried out in a nitrogen atmosphere using a Q200 scanning calorimeter (TA Instruments, USA). Samples of approximately 1 mg were tested in the temperature range from − 30 to 210 °C. Due to the nature of the samples and the need to use several layers of material in one measuring crucible, the samples were heated to 210 °C in the initial stage of the test and kept at this temperature for 1 min. The sample was then cooled to − 30 °C and reheated to 210 °C. In both cases, the temperature change rate was 10 ºC/min. From the cooling and second heating curves, glass transition temperature (T g ), crystallization temperature (T c ), change in enthalpy of the crystallization process (ΔH c ), cold crystallization temperature (T cc ), change in enthalpy of the cold crystallization process (ΔH cc ), melting point (T m ), change in enthalpy melting process (ΔH m ) and the degree of crystallinity (X c ) were determined. The X c values were calculated from the formula: Thermogravimetric analysis was carried out in a nitrogen atmosphere using the Q500 thermal balance (TA Instruments, USA). Samples of approximately 1 mg were tested in the temperature range from room temperature to 600 °C with a temperature change rate of 10 °C/min. Based on thermogravimetric curves, the values of T 5% , T 50% and T 95% corresponding to the temperature of 5, 50 and 95% loss of the initial sample mass were determined. From the differential thermogravimetric curve (DTG) (first derivative of the TG curve), the T max values determining the temperature of the fastest mass loss were also determined.
The hydrophilicity of biopolymers surface was evaluated by measuring the water contact angle formed between water drops and the surface of the samples using a DSA 100 goniometer (Krüss GmbH, Germany) equipped with an automatic dosing system for measuring liquid drop was used. Measurements were carried out using water (polar liquid) and diiodomethane (dispersion liquid). A drop of measuring liquid was placed on the surface of the test sample, its volume was constantly increased and at the same time the dynamic contact angle was measured, which in this case was the character of the inflow angle. After 12 measurements of contact angles with each measuring liquid, the smallest and largest values of these angles were rejected. The arithmetic mean was calculated from the remaining 10 values. Surface energy (SE) was calculated using Neumann method. The formula for the Neumann method applied to SE was in the following form: where ϒ S -SE of polymer sample, ϒ L _ SE of water, and β = 0.0001247 (equation parameters).

Statistical analysis.
Statistical evaluation of all data was conducted using the STATISTICA v.13.1 (StatSoft, Inc, Tulsa, OK, USA). All samples were analyzed in triplicate. The Mann-Whitney U-test was used to determine the significance of differences in PHAs yield and biomass between experimental variants. Data were reported as the median ± SD at the significance level of P < 0.05. Spearman's correlation analysis was carried out with a significance threshold of α = 0.05.

Data availability
All data generated or analyzed during this study are present in the paper (and its Supplementary Information files).


Direct Identification of Urinary Tract Pathogens by MALDI-TOF/TOF Analysis and De Novo Peptide Sequencing

For mass spectrometry-based diagnostics of microorganisms, matrix-assisted laser desorption ionization time-of-flight mass spectrometry (MALDI-TOF MS) is currently routinely used to identify urinary tract pathogens. However, it requires a lengthy culture step for accurate pathogen identification, and is limited by a relatively small number of available species in peptide spectral libraries (≤3329). Here, we propose a method for pathogen identification that overcomes the above limitations, and utilizes the MALDI-TOF/TOF MS instrument. Tandem mass spectra of the analyzed peptides were obtained by chemically activated fragmentation, which allowed mass spectrometry analysis in negative and positive ion modes. Peptide sequences were elucidated de novo, and aligned with the non-redundant National Center for Biotechnology Information Reference Sequence Database (NCBInr). For data analysis, we developed a custom program package that predicted peptide sequences from the negative and positive MS/MS spectra. The main advantage of this method over a conventional MALDI-TOF MS peptide analysis is identification in less than 24 h without a cultivation step. Compared to the limited identification with peptide spectra libraries, the NCBI database derived from genome sequencing currently contains 20,917 bacterial species, and is constantly expanding. This paper presents an accurate method that is used to identify pathogens grown on agar plates, and those isolated directly from urine samples, with high accuracy.

Introduction
In clinical microbiology, methods and techniques for reliable, direct identification of pathogens in human body fluids are continuously investigated. Mass spectrometry-based methods, especially matrix-assisted laser desorption ionization time-of-flight mass spectrometry (MALDI-TOF MS), have been successfully used in routine clinical characterization of pathogens for the past decades [1]. In most cases, competing methods for microbial identification include 16S ribosomal rRNA gene sequencing [2] and real-time polymerase chain reaction (RT-PCR) [3]. Although 16S rRNA sequencing is a widely used method to study the phylogenetic relationships among bacteria, it has low discriminatory power between related species [4]. Another DNA-based method commonly used in clinical practice to identify pathogens is the RT-PCR method. It is a rapid and sensitive method that allows high-throughput analysis, and even the quantification of pathogens [5]. However, the primers of RT-PCR target one or more bacterial species, so non-targeted pathogens cannot be identified. Spectroscopic methods such as Fourier transform near-infrared (FT-NIR) [6] and Raman spectroscopy [7] are also applicable for pathogen identification. These methods are rapid, non-invasive, inexpensive, and, therefore, suitable for routine quality control analyzes. However, the aforementioned technologies are limited by low sensitivity, a relatively small number of reference species (approximately 100), strong background interferences (e.g., water), and, finally, the cultivation of microorganisms [8]. Moreover, the interpretation of the spectral data obtained is often ambiguous, and spectroscopic instruments must be coupled with other standard methods to ensure their reliability. Despite all the advantages and disadvantages of the alternative methods, MALDI-TOF MS is the predominant and most reliable technique in clinical practice for the rapid and cost-effective identification of a wide range of pathogens [9].
Standard urine culture analysis is the most sought-after test in clinical laboratories, as urinary tract infections (UTI) affect more than 150 million people worldwide each year. The most common pathogens of UTIs are uropathogenic Escherichia coli, followed by Klebsiella pneumoniae, Proteus mirabilis, Staphylococcus saprophyticus, Enterococcus faecalis, Group B Streptococcus, Pseudomonas aeruginosa, Staphylococcus aureus, and Candida species [9]. The main disadvantage of urine-culture-based identification methods is the long cultivation time (36-72 h) and possible non-specific identification [10]. Due to the high prevalence of urinary tract infections mentioned earlier, improvement of identification methods in terms of speed, accuracy, and more meaningful identification is an ongoing need in clinical microbiology research. Several bottom-up proteomic studies concerning MS/MS microbial identification were published. In these studies, liquid chromatography-tandem mass spectrometry (LC-MS/MS) and database search tools were used to identify pure microbial cultures [11][12][13][14][15]. Using LC-MS/MS and various database search tools, researchers compared experimentally obtained MS/MS spectra of analyzed peptides with the in-silicogenerated peptide fragmentation spectra in the protein database. Although the LC-MS/MS approach to microorganism identification results in accurate and robust species identification, the protein databases used often encounter obstacles due to the small number of available species. The standard identification procedure usually consists of the step of bacterial cultivation, MALDI-TOF MS analysis of proteins in the mass range of 2-20 kDa, and spectral alignment of the obtained signals with the reference spectral library. To speed up the process, and avoid a time-consuming cultivation step, several studies adapted a MALDI-TOF MS method to identify pathogens directly from common clinical samples such as urine [10,[16][17][18][19][20] or a positive blood culture [21][22][23]. However, direct analysis of samples may be subject to low confidence levels due to polymicrobial or human protein interference [17]. In addition, a recent article described a method for direct identification of UTIs using tandem mass spectrometry, machine learning [24], and bottom-up metaproteomic analysis [25].
A widely used, high-resolution LC-MS/MS technique for proteomic analysis is not a standard in clinical research because of the need for highly skilled personnel, long analysis time, and high maintenance costs [26]. Our method utilizes a MALDI-TOF/TOF MS instrument that overcomes some of the limitations of MALDI-TOF MS and LC-MS/MS strategies. Compared with LC-MS/MS, MALDI-TOF MS and MALDI-TOF MS/MS instruments are much easier to integrate into hospital pipelines, because of their relative simplicity of use and lower operating costs. In addition, the MALDI MS technique is less susceptible to contamination than LC-MS/MS [27]. Unlike MS, MS/MS analysis allows sequencing of each peptide individually, so major interferences from human proteins or other protein contaminants do not interfere with bacterial identification. From this point of view, the optimal tool for pathogen identification in clinical microbiology should include the analytical methods MALDI MS and MS/MS. Therefore, the newly developed de novo sequencing identification method in this research is a complementary improvement to the currently available identification techniques.
We present here a novel bottom-up proteomics approach for the direct identification of microorganisms from a urine sample by tandem mass spectrometry using the MALDI-TOF/TOF MS instrument and de novo peptide sequencing ( Figure 1). The method is based on in-solution N-terminal tryptic peptide derivatization by 4-or 5-formyl-1,3benzenedisulfonic acid (FBDSA), which is described in detail elsewhere [28][29][30]. Derivatization allows de novo sequencing of positive and negative peptide mass spectra obtained after analysis of MALDI-MS/MS. Newly developed software called Protein Acrobat calculates the most probable peptide sequences from the aligned negative MS/MS and positive MS/MS mass spectra using a graph-based algorithm. The resulting list of probable peptides was aligned with the NCBInr database using the protein basic local alignment search tool (BLASTp) [31], and the results were scored according to the expected (E) value. Derived peptides above the predefined E-value threshold were assigned to a species in the database using a peptide-matching algorithm based on the Apache Lucene search engine [32]. The presented positive and negative de novo peptide sequencing approach was applied to the identification of UTI pathogens directly from urine samples. novo sequencing identification method in this research is a complementary improvement to the currently available identification techniques. We present here a novel bottom-up proteomics approach for the direct identification of microorganisms from a urine sample by tandem mass spectrometry using the MALDI-TOF/TOF MS instrument and de novo peptide sequencing ( Figure 1). The method is based on in-solution N-terminal tryptic peptide derivatization by 4-or 5-formyl-1,3-benzenedisulfonic acid (FBDSA), which is described in detail elsewhere [28][29][30]. Derivatization allows de novo sequencing of positive and negative peptide mass spectra obtained after analysis of MALDI-MS/MS. Newly developed software called Protein Acrobat calculates the most probable peptide sequences from the aligned negative MS/MS and positive MS/MS mass spectra using a graph-based algorithm. The resulting list of probable peptides was aligned with the NCBInr database using the protein basic local alignment search tool (BLASTp) [31], and the results were scored according to the expected (E) value. Derived peptides above the predefined E-value threshold were assigned to a species in the database using a peptide-matching algorithm based on the Apache Lucene search engine [32]. The presented positive and negative de novo peptide sequencing approach was applied to the identification of UTI pathogens directly from urine samples.

Results of Standard Urine Culture Test and Identification of Urine Bacterial Isolates Grown on Blood Agar Plates
A standard urine culture test, described in detail in Materials and Methods, was used to determine the number of viable bacteria in urine specimens from patients with a confirmed UTI. The biochemical test "European Guidelines for Urinalysis" [33] was applied to determine the causative agent of the infection and later comparison with the results of mass spectrometry performed in this research. Urine samples from 33 patients were collected on a workday (medium-sized hospital) using the clean-catch method and yielded a bacterial count of 10 5 colony-forming units (CFU/mL) or more. The samples were used for comparison between direct MALDI-TOF/TOF MS UTI identification and standard urine culture test.
Proof of concept for the MALDI-TOF/TOF MS method for direct identification of UTIs was confirmed and validated on pure urine colonies of E. coli, P. mirabilis, P. aeruginosa, and K. pneumoniae grown on blood agar plates. For each designated species, ten biological replicates were processed and analyzed using MALDI-TOF/TOF MS as described in Materials and Methods. Tandem mass spectra were acquired in positive and negative ion modes, and peptide sequences were determined using the Protein Acrobat de novo sequencing algorithm.

Protein Acrobat De Novo Sequencing Algorithm
The data obtained after positive and negative MS/MS analysis in mascot generic format (MGF) were processed using Protein Acrobat. First, the b-ion series were converted from MS/MS negative to y-ions in MS/MS positive, following a peptide fragmentation rule that the sum of the nominal m/z of the b-ions and the corresponding y-ions equals the nominal value of the precursor mass and the mass of two hydrogen atoms: Both spectra were normalized to account the lower peak intensities in the positive spectrum, which was achieved by dividing the spectra by their respective peak maxima. Peaks with a mass within a specified range (0.01 Da) were merged into a single spectrum to remove redundant peaks from positive and negative MS/MS spectra. Figure 2 shows an example of processing positive and negative MS/MS spectra of the peptide belonging to the putative stress response protein (accession number STS794191) found in K. pneumoniae species. The resulting mass spectrum was converted into a graphical spectrum, in which the nodes represent m/z values. The weighting of each node corresponds to the normalized intensity value. Edges were formed between nodes with a mass difference of any amino acid mass. Dynamic programming techniques were used to find paths between the starting node (zero mass) and the ending node (MS ion m/z mass), using the sum of the maximum node weights as the path score. All possible amino acid sequences were determined and scored relative to the overall peak intensity of fragmented ions. The ten highest scoring peptide sequences were matched to a filtered NCBI nr database using the BLASTp tool integrated with Protein Acrobat. The filtered NCBI nr database consisted of 48 common uropathogenic species adapted from Pinault et al. 2019 [11]. The complete list of the 48 bacteria is shown in Table S1 in the Supplementary Material. The E-value was set in the range of 0.001-1, and was 0.1 depending on how many peptides matched the corresponding species.

Direct Identification of Uropathogenic Bacteria from Urine Samples
To determine the accuracy of the UTI identification results, decision tree learning was used to define the confidence level of bacterial identification. For simplicity, the input dataset was obtained from the analysis of pure colonies of E. coli, P. mirabilis, K. pneumoniae, and P. aeruginosa. The original dataset of 40 measurements (10 replicates for each bacterial species) was expanded using the mixup technique [34]. An expanded dataset defines the confidence level of direct bacterial identification of urine samples as follows: high confidence, medium confidence, and low confidence, denoted by the numbers 3, 2, and 1, respectively. Of the 33 urine samples analyzed, 29 samples are successfully identified. Protein Acrobat results for all urine samples are shown in Table 1. A high-confidence level (score 3) is reported for 22 samples, a medium-confidence level (score 2) for 7 samples, and a low = confidence level (score 1) for 4 samples. The low-confidence level samples are misidentified in three of four cases; K. pneumoniae and C. freundii are identified as E. coli and K. pneuomoniae, respectively. The remaining low-confidence level sample identified as K. aerogenes by the standard urine culture test is not identified by the direct identification method. In other words, it has an equal number of peptide matches with K. aerogenes, K. pneumoniae, Enterobacter kobei, and Enterobacter cloacae species. On the other hand, all samples with a medium-confidence level are correctly matched. Only 1 high-confidence level sample is misidentified (Citrobacter freundii), and the remaining 21 high-confidence level samples match the results of the standard urine culture test. The direct bacterial identification pipeline utilizing MALDI-MS/MS and Protein Acrobat is graphically depicted in Figure S1.

Direct Identification of Uropathogenic Bacteria from Urine Samples
To determine the accuracy of the UTI identification results, decision tree learning was used to define the confidence level of bacterial identification. For simplicity, the input dataset was obtained from the analysis of pure colonies of E. coli, P. mirabilis, K. pneumoniae, and P. aeruginosa. The original dataset of 40 measurements (10 replicates for each bacterial species) was expanded using the mixup technique [34]. An expanded dataset defines the confidence level of direct bacterial identification of urine samples as follows: high confidence, medium confidence, and low confidence, denoted by the numbers 3, 2, and 1, respectively. Of the 33 urine samples analyzed, 29 samples are successfully identified. Protein Acrobat results for all urine samples are shown in Table 1. A high-confidence level (score 3) is reported for 22 samples, a medium-confidence level (score 2) for 7 samples, and a low = confidence level (score 1) for 4 samples. The low-confidence level samples are misidentified in three of four cases; K. pneumoniae and C. freundii are identified as E. coli and K. pneuomoniae, respectively. The remaining low-confidence level sample identified as K. aerogenes by the standard urine culture test is not identified by the direct identification method. In other words, it has an equal number of peptide matches with K. aerogenes, K. pneumoniae, Enterobacter kobei, and Enterobacter cloacae species. On the other hand, all samples with a medium-confidence level are correctly matched. Only 1 high-confidence level sample is misidentified (Citrobacter freundii), and the remaining 21 high-confidence level samples match the results of the standard urine culture test. The direct bacterial identification pipeline utilizing MALDI-MS/MS and Protein Acrobat is graphically depicted in Figure S1.

Discussion
Pathogen identification using tandem mass spectrometry is a developing methodology with promising results. Accurate identification of samples derived from pure colonies is shown in several publications [13,35]. However, the main advantage of this methodology is the possibility to directly use clinical samples, thus, avoiding the lengthy culture step [36]. Direct identification analysis was performed on urine samples with a bacterial count of 10 5 CFU/mL or greater. Accurate identification at bacterial counts less than 10 5 CFU/mL can be achieved using more sensitive nano LC-ESI-MS/MS instruments [24]. However, it is shown that accuracy in the aforementioned studies increases dramatically when a larger amount (>10 5 CFU/mL) of bacteria is present in the urine. In fact, high resolution nanoLC-ESI-MS/MS allows the identification of a larger number of peptides, especially low abundance peptides, resulting in better species discrimination and, thus, better identification.
Extracted proteins from bacterial cultures and urine samples were digested prior to identification. The resulting complex peptide mixtures were separated into 36 fractions prior to mass spectra analysis, to increase proteome coverage and facilitate identification of low abundance proteins [37]. As MALDI-TOF/TOF MS is not coupled to a liquid chromatography system, peptides were separated offline in two dimensions using microchromatography cartridges. A strong anion exchanger, specifically a quaternary ammonium cation (QMA), was chosen as the stationary phase in the first dimension because peptide derivatization with 4-formyl-1,3-benzenedisulfonic acid (Materials and Methods, Section 4.4.), as described, enhances the binding of the peptides to the functional groups of the QMA stationary phase. Six eluted fractions in the first dimension were further separated using a SCX stationary phase, to achieve greater separation of peaks in MS analysis. Using a combination of anion and cation exchange, the samples were fractioned and desalted at the same time, producing a clean sample read for the MS analysis. Although direct UTI identification was achieved in ≤24 h, the protocol can be further accelerated by rapid trypsin digestion [38,39] and MALDI-TOF/TOF MS instruments with 2000 Hz laser repetition rates (10× faster acquisition).
Pure bacterial cultures of E. coli, K. pneumoniae, P. mirabilis, and P. aeruginosa were analyzed in ten replicates to assess the qualitative differences of the identified peptides. Although the method was validated using pure cultures, this study aimed to develop a rapid and accurate protocol for the identification of pathogens directly from urine samples, without prior cultivation. Since direct analysis results in an overall lower peptide count than pure cultures, a classification model was applied to evaluate the confidence level of species identification. It is found that 87.8% of the samples could be correctly assigned with highand medium-confidence levels. Misidentifications occur in samples with low-confidence levels and in one sample with a high-confidence level. The incorrect results involve three samples of Klebsiella species and one C. freundii. The results could be explained by the mixedspecies samples (e.g., two or more species in the sample), contaminated urine samples (e.g., large number of human cells), or the high genomic similarity between Klebsiella, Escherichia, and Citrobacter species [40,41], which makes them difficult to distinguish when only a small number of peptides are identified.
However, it is worth mentioning that the identification of Klebsiella species, which was challenging in direct analysis, was unambiguous when analyzing pure colonies. The identification method was based on de novo sequencing of tryptic peptides, and subsequent peptide sequence alignment with 48 common uropathogenic bacterial species present in the NCBInr database (Table S1). De novo peptide sequencing is a promising identification tool in proteomics that has been investigated over the past 20 years [42]. Despite various de novo sequencing algorithms and extensive research, there is an apparent lack of wider application, especially in the identification of complex protein mixtures [43,44]. This can be attributed to a few drawbacks of MS/MS spectra sequencing such as insufficient mass accuracy relative to non-linear sequences data structure consisting of determined amino acid at nodes and edges (e.g., an average MS/MS spectrum could be branched by the algorithm in several hundred sequences), and uneven fragmentation patterns caused by missing fragment ions. The named drawbacks, along with the noise present in the MS/MS spectra ( Figures S2-S4), hamper the complete detection of long sequences (larger than 20 amino acids), and contribute to sequence ambiguities. Disulfonic peptide derivatization at the N-terminus improves amino acid sequence recognition, by allowing the revelation of only b-ions in negative ion mode MS/MS, and y-ions in positive ion mode MS/MS [45]. The de-novo-identified peptides were aligned with protein sequences in the database, and microorganism species were determined based on the highest number of matched peptides. The described identification method can also be used to identify other pathogens in clinical, environmental, or food samples. However, rare pathogens or other species of interest could be identified by searching the entire NCBInr database, which increases the search time but, on the other hand, allows the identification of virtually any species in the database.

Urine Sample Collection Ethics
Clean-voided, midstream urine specimens were collected from outpatients who were referred for urine culture and analysis to the Department for Clinical Microbiology and Hospital Infections, University Hospital Dubrava, Zagreb, Croatia. The urine samples were tested for bacterial growth on culture plates. The number of bacteria was determined by colony counting on an agarose MacConkey plate, and the species were determined by biochemical identification, according to standard procedures [33].

Protein Extraction
Bacterial colonies from agar plates were collected with a microbiological loop and mixed with 400 µL of 50 mM ammonium bicarbonate. The bacterial suspension was centrifuged at 8000× g for 10 min at 4 • C to wash the cells, and the supernatant was discarded. Proteins extracted directly from urine samples were obtained by the following protocol: a volume of 15 mL of thawed urine sample was centrifuged at 500× g for 1 min at room temperature, to separate microbial cells from larger particles such as salt crystals and leukocytes. The supernatant was centrifuged at 4500× g for 30 min at 4 • C to obtain bacterial pellet, which was then resuspended in 400 µL of 50 mm ammonium bicarbonate, and again centrifuged at 8000× g for 10 min at 4 • C. The wash step with ammonium bicarbonate was repeated one more time. From this point on, further sample preparation protocol and analysis were the same for bacterial biomass obtained from pure colonies and urine samples.
Cell lysis was achieved by resuspending the bacterial pellet in 200 µL of lysis buffer containing 2% of sodium SDS, 100 mm Tris/HCl pH 7.8, and 0.1 M DTT. After incubation at room temperature for 10 min, cells were disrupted by sonication using the Sonoplus mini20 ultrasonic homogenizer (Bandelin, Berlin, Germany). Samples were sonicated for five cycles of 1 min, with a 30 s cooling interval between cycles, and the sonication amplitude was set to 50%. Afterwards, samples were placed into boiling water for 2 min to inhibit protease activity. The cell lysate was removed from each sample by centrifugation at 16,000× g for 20 min at 4 • C, and the protein fraction contained in supernatant was further processed.

Protein Purification and Digestion
The FASP protocol was adapted from Yu et al., and conducted with slight modifications [46]. In brief, the Microcon centrifugal filter devices were rinsed with 200 µL of ultrapure water and 200 µL urea solution (8 M urea in 100 mm Tris/HCL buffer). An aliquot of 100 µL of extracted protein mixture was added to a filter device, mixed with 200 µL of urea solution, and centrifuged at 12,000× g for 20 min at 20 • C. Flow through was discarded, and 200 µL of urea solution was added to a filter and spun at 12,000× g for 15 min at 20 • C. This step was repeated, and filter was further washed twice with 200 µL of ammonium bicarbonate buffer. Tryptic digestion was performed overnight by adding 2 µL of 1 mg/mL trypsin solution and 100 µL of ammonium bicarbonate buffer to the filter unit, and incubating the resulting solution overnight on a Comfort thermomixer (Eppendorf, Hamburg, Germany) at 37 • C and 500 rpm. After digestion, peptides were centrifuged of the filter device at 12,000× g for 15 min, followed by one wash step with 50 µL of ammonium bicarbonate buffer. The peptide solution was dried in vacuum concentrator at 30 • C.

Derivatization Procedure
Peptide derivatization procedure was previously described [29], and repeated here with modifications. Each sample containing dried tryptic peptides was reconstituted with 30 µL of derivatization solution. The derivatization solution contained 12.5 mM of 4-formyl-1,3-benzenedisulfonic acid disodium salt hydrate and 95.5 mm of sodium cyanoborohydride dissolved in 10 mm potassium dihydrogen phosphate pH 5. The derivatization was performed in a household microwave oven at 180 W for 8 min.

Two Dimensional Fractionation of Peptide Mixture
Sample fractionation was performed by AssayMAP Bravo Automated liquid handling platform (Agilent, St. Clara, CA, USA), using a pre-determined fractionation protocol. Dried peptides were reconstituted in 1% of ammonium hydroxide, and subjected to a strong anion exchange using QMA stationary phase. The stationary phase was transferred to a 5 µL resin-free cartridges. Eluted fractions were dried in a vacuum concentrator, then resuspended in 1% formic acid, and additionally fractioned by SCX stationary phase, according to the manufacturer's protocol. Buffers used for QMA and SCX fractionation are shown in Table S2 in Supplementary Materials. Finally, the resulting 36 fractions from each sample were evaporated in a vacuum concentrator.

Mass Spectrometry
Dried peptide fractions were resuspended in 10 µL of 5 mg/mL CHCA dissolved in 50% acetonitrile, and a volume of 1 µL was spotted onto a MALDI plate. Mass spectrometry acquisition was performed with a MALDI-TOF/TOF MS 4800 Plus analyser (AB Sciex, Framingham, MA, USA) equipped with a 200 Hz, 355 nm neodymium-doped yttrium aluminium garnet Nd: YAGlaser. Ions in MS analysis were analyzed in reflectron negative ion mode. The instrument parameters were set using the 4000 Series Explorer software V 3.5.3 (AB Sciex, Framingham, MA, USA). Mass spectra were obtained by averaging 1800 laser shots covering a mass range of m/z 1000 to 4000. The precursor ions generated by negative ion MS were analyzed both in negative and positive MS/MS ion mode. Tandem mass spectrometry acquisition was achieved by 1 kV collision energy, without usage of collision gas. Precursor peak selection (LC-MALDI peak MS processing) was controlled by job-wide peak selection method. Peak selection was performed automatically, in order to analyze the MS spectra and acquire MS/MS data from selected peaks. Parameters of MS/MS peak selection were as follows: minimum S/N filter = 15, minimum chromatogram peak width = 3, maximum precursors per fraction = 20, fraction-to-fraction precursor mass tolerance = 200 ppm.

BLASTp Parameters
Parameters of the blast search were as follows: amino acid mass tolerance = 0.3; number of queries = 10; matrix = PAM30; word size = 2; window size = 40; threshold = 11; gap cost existence = 9; gap costs extension = 1. The E-value was set to 0.1, in order to show only relevant results. Peptides were matched to a custom urinary database by an in-house-developed application written in C#, which utilizes Apache-Lucene-based search engine as it is described elsewhere [32]. The results were grouped by the number of queries (peptides) matched to a species in the database where the highest number of peptide matches correspond to an identified species.

Conclusions
We successfully applied a bottom-up mass spectrometry approach to identify bacterial species causing urinary tract infections directly from urine samples. Overall, the identification of pathogens causing urinary tract infections is achieved within 24 h, without a prior cultivation step. A novel de novo peptide sequencing software was developed to provide accurate identification even when processing a large search database. Furthermore, a mathematic model was applied to estimate the reliability of the identification result. Taxonomic resolution was satisfactory, however, it can be improved with the use of more sensitive instrumentation and curated database. In addition to urinary tract infections, the strategy used in this study could also be used for the analysis of other clinical samples such as blood cultures and stool samples, therefore, providing a path for further improvement of widely used MALDI MS techniques (MALDI MS to MALDI MS/MS) in clinical microbiology.
Supplementary Materials: The following supporting information can be downloaded at: https: //www.mdpi.com/article/10.3390/molecules27175461/s1, Figure S1: Workflow of five-step MALDI MS/MS identification of urine microorganisms. Figure S2: Mass spectra negative ion mode total signal-to-noise intensity per spot m/z 1000-3500. Figure S3: Tandem mass spectra negative ion mode total MS/MS signal-to-noise intensity per selected precursor ion spectrum. Figure S4: Tandem mass spectra positive ion mode total MS/MS signal-to-noise intensity per selected precursor ion spectrum.  Funding: This research was funded by the European Regional Development Fund "Qua/Qua" project, grant number KK.01.1.1.07.0023.

Institutional Review Board Statement:
The study was conducted in accordance with the Declaration of Helsinki, and approved by the Ethics Committee of University Hospital Dubrava (protocol name "Identification of Uropathogens to a Sub-Species Level Directly from Urine Samples Using Mass Spectrometry", 13 November 2019).
Informed Consent Statement: Written informed consent was obtained from the patients to publish this paper.
Data Availability Statement: All data are provided in the Supplementary Materials or are available on request.

Conflicts of Interest:
The authors declare no conflict of interest.